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News
June 5, 2026
Neural Network Maps as a Method for Constructing Mathematical Models
Scientists from HSE University–Nizhny Novgorod and the Institute of Physics Belgrade, Serbia, are jointly exploring the application of machine learning techniques and neural networks to the study of nonlinear dynamics. Natalya Stankevich, Leading Research Fellow at the Laboratory of Topological Methods in Dynamics of the Faculty of Informatics, Mathematics, and Computer Science at HSE University–Nizhny Novgorod, spoke to the HSE News Service about this international project.
June 5, 2026
‘In the Age of Technology, It Is Interesting to Look into the Past and Think about What We Can Take from It
Polina Tabakova decided to apply for a Philology degree at HSE in Nizhny Novgorod because she grew up in Mari El and did not want to move far away from the Russian forests. In an interview for the Young Scientists of HSE University project, she spoke about the genre of the campus novel, the existential drama of Kolobok, and a blackout version of Eugene Onegin.
June 5, 2026
HSE Scientists Develop Method to Compress Large Language Models Without Losing Quality
Researchers from the AI and Digital Science Institute at the HSE Faculty of Computer Science have developed a new compression method for large language models such as GPT and LLaMA that reduces their size by 25–36% without additional training or significant loss of accuracy. This is the first approach to use mathematical transformations—specifically, rotations of model weights—to make models more amenable to compression with structured matrices. The study results have been published in ACL Findings 2025. The code is available on GitHub.

 

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Прогнозирование интенсивности послеоперационного болевого синдрома у пациенток, перенесших экстирпацию матки

Регионарная анестезия и лечение острой боли. 2018. Т. 12. № 3. С. 167–174.
Смирнова О. В., Генов П. Г., Тимербаев В. Х., Тукибаева Т. Ф., Rebrova O.

The problem of postoperative analgesia don’t lose it’s relevance despite the large implementation in practice the multimodal analgesia strategy. In prescribing the analgesia in the most cases don’t consider the predictors of intensive postoperative pain, which could to contribute the choice of ineffective postoperative analgesia. Purpose. The determination of predictors of intensive pain after hysterectomy. Materials and methods. We have observed women from 18 to 70 years old which have undergone a hysterectomy under general anesthesia. We have studied socio-demographic data, the presence of chronic abdominal pain before surgery, pain threshold and pain tolerance, type of surgical access and pain expectation. Results. A mathematical model was developed for predicting a moderate and severe (> 40 mm visual analogue scale) dynamic pain 2 hours after the operation with a 60% cut-off point, implemented as a calculator in MS Excel. As a set of predictors, the following signs were used: the presence of pain in the lower abdomen before the operation, tolerance to pain, the expected pain intensity and the type of surgical access. The predictive value of the positive model result was 79%, CI [69%, 86%]. Conclusion. Women who have a prediction of moderate and severe pain after the extirpation of the uterus are 60% or more likely to develop it, in order to achieve adequate analgesia, it may be recommended to use more intensive postoperative analgesia, including using regional techniques, which will improve the quality of postoperative analgesia.

Research target: Clinical Medicine Medical Technologies Computer Science Mathematics
Priority areas: IT and mathematics
Language: Russian
Text on another site
Keywords: painбольобезболиваниеhysterectomyэкстирпация маткиpredictorsпослеоперационная больpostoperative painanalgesiaфакторы прогноза
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